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原文標題：
GLM-5: From Vibe Coding to Agentic Engineering

原文連結：
https://z.ai/blog/glm-5

發布時間：
2026-02-12

記者署名：
無
※原文無記載者得留空

原文內容：
We are launching GLM-5, targeting complex systems engineering and long-horizon a
gentic tasks. Scaling is still one of the most important ways to improve the int
elligence efficiency of Artificial General Intelligence (AGI). Compared to GLM-4
.5, GLM-5 scales from 355B parameters (32B active) to 744B parameters (40B activ
e), and increases pre-training data from 23T to 28.5T tokens. GLM-5 also integra
tes DeepSeek Sparse Attention (DSA), significantly reducing deployment cost whil
e preserving long-context capacity.


Reinforcement learning aims to bridge the gap between competence and excellence
in pre-trained models. However, deploying it at scale for LLMs is a challenge du
e to RL training inefficiency. To this end, we developed slime, a novel asynchro
nous RL infrastructure that substantially improves training throughput and effic
iency, enabling more fine-grained post-training iterations. With advances in bot
h pre-training and post-training, GLM-5 delivers significant improvement compare
d to GLM-4.7 across a wide range of academic benchmarks and achieves best-in-cla
ss performance among all open-source models in the world on reasoning, coding, a
nd agentic tasks, closing the gap with frontier models.



心得/評論：
https://i.meee.com.tw/DAfKbgq.jpg

智譜 (2513.HK) 發布了新一代大模型 GLM-5，基準測試已超越 Google 的 Gemini 3 系列
，僅次於 Claude Opus 4.6 與 GPT-5.2 (深度思考模式)。

作為全球首個上市的純AI模型公司，上市後的第一個旗艦模型依舊維持MIT開源，任何人現
在都能下載直接用，這要怎麼賺錢？不過市場看起來很熱烈，早盤最高達到+33%了。




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※ 作者: h0103661 2026-02-12 12:02:58
※ 文章代碼(AID): #1fZL3v94 (Stock)
※ 文章網址: https://www.ptt.cc/bbs/Stock/M.1770868985.A.244.html